Staging of Alzheimer's disease progression in Down syndrome using mixed clinical and plasma biomarker measures with machine learning.

ABSTRACT:

Introduction

Adults with Down syndrome (DS) have a high risk for Alzheimer's disease (AD). Although the sequence of plasma biomarker and cognitive changes in AD in DS is well studied, their related trajectories are not fully characterized. Data-driven methods can estimate disease progression from cross-sectional data.

Methods

In 57 adults with DS and no AD, we used the event-based model to sequence plasma biomarker and cognitive changes in preclinical AD. Generalized additive models assessed the relationship between age and plasma biomarkers.

Results

The earliest changes occurred in the amyloid beta 42/40 ratio, followed by memory changes. Later alterations in neurofilament light and tau concentrations preceded executive and visuomotor function changes, with glial fib

SUBMITTER: Idris M 

PROVIDER: S-EPMC12276070 | biostudies-literature | 2025 Jul

REPOSITORIES: biostudies-literature